$ETH The market is panicking, but the charts tell a differen | Gladys Lochridge ckrM on Binance Square

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$ETH The market is panicking, but the charts tell a different story.

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$BTC Crypto ETF funds have experienced their fourth consecutive week of outflows, totaling $876 million, the second-highest level after last week's record $3 billion outflow. According to a report from CoinShares, U.S. investors were the most pessimistic, withdrawing $922 million, while most other regions saw this as a buying opportunity.

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#BitcoinBounceBack Bitcoin Dominance Says That Bear Market Is Almost Over For Alts! Today we will take a look at the BTC.D again, this chart is annoying, but is finally approaching its reversal point. Let's take a look at the weekly time frame. Here we can see the 3 red dots on the Bullish/Bearish Reversal Bar Indicator [Skyrexio]. Now we will try to learn now to ignore the false signals. The first dot formed on the very weak bar with no angulation with Alligator. We can's use this. The next bar was great, but it was just the wave 3. The best signal is the last one. We have angulation, bearish divergence with AO and the potential wave 5.

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$BNB BotOrNot Hijacking of social media accounts has become a modern-day danger. Motivations for this can range from attempts in identity theft to simply skewing the perception of an audience. In this paper, we extend our previous work, Engineering Your Social Network to Detect Fraudulent Profiles, by doing an investigation of spam bots on Twitter. We propose an algorithm that will distinguish a spam bot, from a genuine user account by using a JavaScript testing framework that consumes Twitter's REST API. We ran a dataset of 700 Twitter accounts through our algorithm and identified that roughly 11% of the dataset were bot

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#BotOrNot BotOrNot Hijacking of social media accounts has become a modern-day danger. Motivations for this can range from attempts in identity theft to simply skewing the perception of an audience. In this paper, we extend our previous work, Engineering Your Social Network to Detect Fraudulent Profiles, by doing an investigation of spam bots on Twitter. We propose an algorithm that will distinguish a spam bot, from a genuine user account by using a JavaScript testing framework that consumes Twitter's REST API. We ran a dataset of 700 Twitter accounts through our algorithm and identified that roughly 11% of the dataset were bot

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$BNB Warning...!!! The following post is not an investment advice. Hello all , Eventhough I have used the hashtag FollowTheLeadTrader I request each and everyone reading this post not to follow anyone blindly. Every trader will have his/her own trading strategy which is suitable only to the amount of capital and financial backup of their own. A person with a total networth of 1M $ will be ok even if he happens to loose 5-10 K $ in a bear market but that doesn't suit a person with a total capital 5-10 K $. So , one must always do his/her own research before taking a position in any asset.

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